A relation enhanced model for temporal knowledge graph alignment-Reference-Cited by-同舟云学术

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A relation enhanced model for temporal knowledge graph alignment

Published:2023-10-06 Issue: Volume: Page:
ISSN:0920-8542
Container-title:The Journal of Supercomputing
language:en
Short-container-title:J Supercomput

Author:

Wang Zhaojun,You Xindong,Lv Xueqiang

Funder

Natural Science Foundation of Beijing

National Language Commission project

R&D Program of Beijing Municipal Education Commission

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Hardware and Architecture,Information Systems,Theoretical Computer Science,Software

Link

https://link.springer.com/content/pdf/10.1007/s11227-023-05670-w.pdf

Reference60 articles.

1. Rebele T, Suchanek F, Hoffart J, Biega J, Kuzey E, Weikum G (2016) YAGO: a multilingual knowledge base from Wikipedia, wordnet, and geonames. In: The Semantic Web–ISWC 2016: 15th International Semantic Web Conference, Kobe, Japan, October 17–21, 2016, Proceedings, Part II 15. Springer, pp 177–185

2. Auer S, Bizer C, Kobilarov G, Lehmann J, Cyganiak R, Ives Z (2007) DBpedia: a nucleus for a web of open data. In: The Semantic Web: 6th International Semantic Web Conference, 2nd Asian Semantic Web Conference, ISWC 2007+ ASWC 2007, Busan, Korea, November 11–15, 2007. Proceedings. Springer, pp 722–735

3. Bollacker K, Evans C, Paritosh P, Sturge T, Taylor J (2008) Freebase: a collaboratively created graph database for structuring human knowledge. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp 1247–1250

4. Cao Y, Wang X, He X, Hu Z, Chua T-S (2019) Unifying knowledge graph learning and recommendation: towards a better understanding of user preferences. In: The World Wide Web Conference, pp 151–161

5. Zheng W, Yu JX, Zou L, Cheng H (2018) Question answering over knowledge graphs: question understanding via template decomposition. Proc VLDB Endow 11(11):1373–1386

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